LFM2 24B needs ~20.7 GB VRAM. RTX A5000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~37 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Tight fit
Decode
39.5 tok/s
TTFT
4904 ms
Safe context
38K
Memory
20.7 GB / 24.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 36.7 tok/s | 2876 ms | 38K |
| Coding | A | Tight fit | 36.7 tok/s | 5272 ms | 38K |
| Agentic Coding | A | Runs with offload | 36.7 tok/s | 7669 ms | 38K |
| Reasoning | A | Tight fit | 36.7 tok/s | 6231 ms | 38K |
| RAG | A | Runs with offload | 36.7 tok/s | 9586 ms | 38K |
How LFM2 24B (24B params) fits at each quantization level on RTX A5000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | A82 |
Q3_K_S | 3 | 11.8 GB | Low | A83 |
NVFP4 | 4 |
Copy-paste commands to run LFM2 24B on your machine.
Run
ollama run lfm2Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 81.3 tok/s | ||
| 27B | S | 35.3 tok/s |
Yes, RTX A5000 24GB can run LFM2 24B with a A grade (Tight fit). Expected decode speed: 36.7 tok/s.
LFM2 24B (24B parameters) requires approximately 20.7 GB of memory with Q4_K_M quantization.
The recommended quantization for LFM2 24B is Q4_K_M, which balances quality and memory efficiency.
On RTX A5000 24GB, LFM2 24B achieves approximately 36.7 tokens per second decode speed with a time-to-first-token of 5272ms using Q4_K_M quantization.
For coding workloads, LFM2 24B on RTX A5000 24GB receives a A grade with 36.7 tok/s and 38K context.
On RTX A5000 24GB, LFM2 24B can safely use up to 38K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/lfm2-24b-on-a5000-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
13.4 GB |
| Medium |
| A83 |
Q4_K_M | 4 | 14.6 GB | Medium | A83 |
Q5_K_MBest for your GPU | 5 | 17.3 GB | High | A83 |
Q6_K | 6 | 19.7 GB | High | F0 |
Q8_0 | 8 | 25.7 GB | Very High | F0 |
F16 | 16 | 49.2 GB | Maximum | F0 |
| 27B | S | 35.4 tok/s |
| 30B | S | 84.1 tok/s |
| 35B | A | 45.5 tok/s |